Identification of novel PI3Kδ inhibitors by docking, ADMET prediction and molecular dynamics simulations

Ya-Ya Liu; Xiao-Yan Feng; Wen-Qing Jia; Zhi Jing; Wei-Ren Xu; Xian-Chao Cheng

doi:10.1016/j.compbiolchem.2018.12.002

Identification of novel PI3Kδ inhibitors by docking, ADMET prediction and molecular dynamics simulations

Comput Biol Chem. 2019 Feb:78:190-204. doi: 10.1016/j.compbiolchem.2018.12.002. Epub 2018 Dec 7.

Authors

Ya-Ya Liu¹, Xiao-Yan Feng¹, Wen-Qing Jia¹, Zhi Jing¹, Wei-Ren Xu², Xian-Chao Cheng³

Affiliations

¹ Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin 300070, China.
² Tianjin Key Laboratory of Molecular Design and Drug Discovery, Tianjin Institute of Pharmaceutical Research, Tianjin 300193, China.
³ Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin 300070, China. Electronic address: chengxianchao@aliyun.com.

PMID: 30557817
DOI: 10.1016/j.compbiolchem.2018.12.002

Abstract

Background: Phosphoinositide-3-kinase Delta (PI3Kδ) plays a key role in B-cell signal transduction and inhibition of PI3Kδ is confirmed to have clinical benefit in certain types of activation of B-cell malignancies. Virtual screening techniques have been used to discover new molecules for developing novel PI3Kδ inhibitors with little side effects.

Method: Computer aided drug design method were used to rapidly screen optimal PI3Kδ inhibitors from the Asinex database. Virtual screening based molecular docking was performed to find novel and potential lead compound targeting PI3Kδ, at first. Subsequently, drug likeness studies were carried out on the retrieved hits to evaluate and analyze their drug like properties such as absorption, distribution, metabolism, excretion, and toxicity (ADMET) for toxicity prediction. Three least toxic compounds were selected for the molecular dynamics (MD) simulations for 30 ns in order to validate its stability inside the active site of PI3Kδ receptor.

Results: Based on the present in silico analysis, two molecules have been identified which occupied the same binding pocket confirming the selection of active site. ASN 16296138 (Glide score: -12.175 kcal/mol, cdocker binding energy: -42.975 kcal/mol and ΔG_bind value: -90.457 kcal/mol) and BAS 00227397 (Glide score: -10.988 kcal/mol, cdocker binding energy: -39.3376 kcal/mol and ΔG_bind value: -81.953 kcal/mol) showed docking affinities comparatively much stronger than those of already reported known inhibitors against PI3Kδ. These two ligand's behaviors also showed consistency during the simulation of protein-ligand complexes for 30000 ps respectively, which is indicative of its stability in the receptor pocket.

Conclusion: Compound ASN 16296138 and BAS 00227397 are potential candidates for experimental validation of biological activity against PI3Kδ in future drug discovery studies. This study smoothes the path for the development of novel leads with improved binding properties, high drug likeness, and low toxicity to humans for the treatment of cancer.

Keywords: ADMET analysis; Docking; PI3Kδ inhibitors; Prime MM/GBSA; Virtual screening.

MeSH terms

Class I Phosphatidylinositol 3-Kinases / antagonists & inhibitors
Class I Phosphatidylinositol 3-Kinases / metabolism
Computer-Aided Design*
Drug Discovery
Drug Evaluation, Preclinical
Humans
Ligands
Molecular Docking Simulation*
Molecular Dynamics Simulation*
Molecular Structure
Protein Kinase Inhibitors / chemistry*
Protein Kinase Inhibitors / metabolism
Protein Kinase Inhibitors / pharmacology
Skin / drug effects
Small Molecule Libraries / chemistry*
Small Molecule Libraries / metabolism
Small Molecule Libraries / pharmacology
Thermodynamics

Substances

Ligands
Protein Kinase Inhibitors
Small Molecule Libraries
Class I Phosphatidylinositol 3-Kinases
PIK3CD protein, human